Data BAU Lead – Data Engineering
Summary
Lead a team to maintain and improve cloud-based data pipelines, warehouses, and lakes, migrating legacy systems to Snowflake and AWS Glue while ensuring stability and performance.
We are looking for an experienced Data BAU Lead to lead data engineering operations, production support, and continuous improvement in a cloud-first environment.
Key Responsibilities
- Lead a team of data engineers managing BAU operations, production support, incidents, and platform stability.
- Design, develop, and support scalable data pipelines, data feeds, data lakes, and data warehouses.
- Drive migration of legacy Oracle, MS-SQL, Hive, and Impala workloads to Snowflake, Spark, and AWS Glue.
- Work closely with business, architects, data scientists, and DevOps teams to deliver data solutions.
- Improve data quality, performance, monitoring, automation, and operational efficiency.
- Support data strategy, architecture, security, and governance initiatives.
Key Skills & Experience
- 7+ years of data engineering experience, including 2+ years in hands-on lead/production support roles.
- Strong expertise in AWS – S3, Glue, DMS, MWAA/Airflow, IAM, Lambda, RDS, Kinesis, and Step Functions.
- Strong Snowflake expertise and data warehouse/data lake experience.
- Hands-on programming skills in SQL, Python, PySpark, Spark, and Unix Shell.
- Experience with ETL, data ingestion, data integration, distributed systems, and large-scale datasets.
- Strong understanding of CI/CD, Git, Agile/SDLC, and cloud optimization.
- Proven experience in team leadership, stakeholder management, and production/BAU environments.
- Bachelor’s degree in Computer Science, Engineering, STEM, or related field